Answers for COOs and automation leaders.
Direct responses to the questions COOs, operations and transformation leaders ask — each backed by first-party benchmarks and reviewed 2026-08-31.
9 answers
What is AI business automation?
AI business automation applies models, retrieval and agents to end-to-end operational workflows — claims, invoices, onboarding, records, case handling — so documents are read, decisions are drafted and systems are updated without a person touching every step. People handle exceptions and approvals. The measurable outcome is straight-through processing rate and cost per transaction, not tasks automated.
RPA or agentic automation — what is the difference?
RPA executes deterministic, pre-scripted steps and breaks when screens or formats change. Agentic automation reasons over unstructured input, chooses tools and adapts, but needs guardrails, permissions and evaluation. Use RPA for stable, high-volume mechanics and agents for judgement and variation — most production workflows combine both, with agents deciding and RPA or APIs executing.
How do you automate insurance claims processing with AI?
Automate claims in four steps: ingest and classify the submission, extract structured data from documents and images, triage by complexity and fraud signal, and settle low-complexity claims straight through while routing the rest to adjusters with a drafted summary. Accuracy gates and sampled human review protect leakage while the straight-through share increases.
How do BPOs protect margin with AI?
BPOs protect margin by automating the work that clients already expect to cost less, consolidating onto fewer platforms, and using AI quality assurance to cover every interaction instead of a sample. As pricing shifts from seats to outcomes, margin follows automation share and cost per transaction rather than headcount utilisation.
How do you get 100% quality assurance coverage in a contact center?
AI quality assurance scores every interaction against your existing scorecard instead of the small manual sample most centres review. Calibrate the model against human scores on a labelled set, publish agreement rates, then move QA analysts from listening to coaching and dispute review. Full coverage removes sampling bias and surfaces compliance risk that sampling misses.
How should a COO evaluate AI business automation?
A COO should evaluate AI business automation on straight-through processing rate, exception handling cost and total cost per transaction — not on how many tasks are automated. The best programmes define the success signal in the system of record, design the exception path before the happy path, and measure against a pre-automation baseline that finance can reproduce.
How do you implement AI business automation?
Start with process selection rather than technology: score candidates on volume, document dependency, exception rate, decision reversibility and system access. Then build five reusable layers — document intelligence, governed retrieval, an entitlement-aware tool layer, orchestration with human routing, and evaluation with production tracing. The first workflow funds the platform; every later workflow reuses it at marginal cost.
How can AI automate finance operations?
Finance operations automate where the work is document-driven and rule-governed: invoice and remittance capture, three-way matching, coding and approval routing, collections correspondence, and reconciliation during the close. The pattern is extraction with a citation to the source document, validation against master data, straight-through processing inside policy limits, and routing of everything else to a reviewer with the evidence attached.
How do you calculate back-office automation ROI?
Measure cost per case before anything is built: fully loaded handling time, rework, and the cost of errors caught downstream. Model value from three levers — straight-through processing rate, reduced review time on the remainder, and error reduction — then subtract platform, integration, evaluation and run cost. Claim only savings the operating plan can realise, because capacity released is not cash saved until headcount, backlog or growth absorbs it.